Applied AI Summit Healthcare
Free online conference | April 14-15, 2026Accelerating AI-enabled Drug Discovery with AI-ready Teaming
Accelerating AI-enabled drug discovery requires more than stronger models — it requires AI-ready teaming that makes data, tools, and expertise interoperable, trusted, and reusable. The SmartDrugDiscovery network, led by the Systems Pharmacology AI Research Center (SPARC) at UAB, is building an open, disease-focused ecosystem where communities define priorities: shared benchmarks, transparent evaluation, and reproducible workflows that reduce duplication and improve translation.
Building on lessons from CM4AI and NIH ecosystem efforts including Bridge2AI and CFDE, this talk presents a practical blueprint for “Drug Discovery 2.0” that healthcare stakeholders can adopt today:
- A community governance model for responsible AI
- A reference stack for connecting datasets to validated pipelines
- A Talent Knowledge Graph that rapidly assembles cross-disciplinary teams around specific diseases and development questions
We close with a partnership playbook for industry–academia co-development of open-source infrastructure that speeds impact while lowering risk.
About the speaker
Jake Chen
Professor and Director
at Systems Pharmacology AI Research Center, the University of Alabama at Birmingham
Dr. Jake Y. Chen is the Triton Endowed Professor of Biomedical Informatics and Data Science at the UAB School of Medicine, with joint appointments in Genetics, Computer Science, and Biomedical Engineering, and is the founding director of the Systems Pharmacology AI Research Center (SPARC).
Over 25 years, he has advanced AI-driven biomedical informatics, network/systems biology, and computational drug discovery—developing systems pharmacology models, multi-omics AI frameworks, and digital twin simulations that integrate clinical, genomic, and real-world data for precision medicine. He has 200+ peer-reviewed publications and 200+ invited talks worldwide.
Dr. Chen also leads and convenes large, multi-institutional collaborations and contributes to national biomedical AI strategy and translational informatics infrastructure. He serves as the Contact MPI for CONNECT, an NIH U54-funded national AI-infrastructure initiative (2024–2029) focused on building AI-ready biomedical knowledge networks and has advised NIH and the U.S. Congress (via NIDDK panels) while collaborating with FDA efforts related to AI-driven biomedical innovation.
A recognized leader in AI-driven systems pharmacology, he is a Fellow of ACMI, AIMBE, and AMIA, an ACM Distinguished Member, and has received honors including the “Top 100 AI Leaders in Drug Discovery and Healthcare” (Deep Knowledge Analytics, 2019) and the CAST-USA Pioneer Award (2023).